An availability determination method, apparatus, electronic device, storage medium, and program product

Abstract

Embodiments of the present application disclose a kind of availability determining method, device, electronic equipment, storage medium and program product.The method comprises: obtaining the first inspection result generated by carrying out availability inspection to target system;First inspection result is monitored index conversion, and first monitoring index is obtained, to determine the availability of target system according to first monitoring index and second monitoring index;Wherein, second monitoring index is generated by monitoring the availability of target system.The technical scheme of the embodiment of the present application can improve the accuracy of the availability determination of target system.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a method, apparatus, electronic device, storage medium and program product for determining availability. Background Technology

[0002] With the widespread application of cloud-native technology systems, hybrid multi-cloud technology architectures, which are based on cloud-native technologies and provide unified infrastructure for applications in a multi-cloud form, are gradually becoming the mainstream technology form.

[0003] Based on this, for target systems running on a hybrid multi-cloud technology architecture (i.e., a hybrid multi-cloud platform), in order to ensure the large-scale application of the hybrid multi-cloud platform, the availability of the target system needs to be determined.

[0004] In the process of realizing this invention, the inventors discovered the following technical problem in the prior art: the availability of the target system cannot be accurately determined, which urgently needs to be solved. Summary of the Invention

[0005] This invention provides an availability determination method, apparatus, electronic device, storage medium, and program product to improve the accuracy of availability determination for a target system.

[0006] According to one aspect of the present invention, an availability determination method is provided, which may include:

[0007] Obtain the first inspection results generated by performing availability inspections on the target system;

[0008] The first inspection results are converted into monitoring indicators to obtain the first monitoring indicator, and the availability of the target system is determined based on the first monitoring indicator and the second monitoring indicator.

[0009] The second monitoring indicator is generated by monitoring the availability of the target system.

[0010] According to another aspect of the present invention, an availability determination apparatus is provided, which may include:

[0011] The first inspection result acquisition module is used to acquire the first inspection result generated by the availability inspection of the target system.

[0012] The availability determination module is used to convert the first inspection results into monitoring indicators to obtain the first monitoring indicator, so as to determine the availability of the target system based on the first monitoring indicator and the second monitoring indicator.

[0013] The second monitoring indicator is generated by monitoring the availability of the target system.

[0014] According to another aspect of the present invention, an electronic device is provided, which may include:

[0015] At least one processor; and

[0016] A memory that is communicatively connected to at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by at least one processor, such that when the at least one processor executes the program, it implements the availability determination method provided in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided having computer instructions stored thereon for causing a processor to execute and implement the availability determination method provided in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer program product is provided, on which a computer program is stored, which, when executed by a processor, implements the availability determination method provided in any embodiment of the present invention.

[0020] The technical solution of this invention involves obtaining a first inspection result generated by performing availability inspection on a target system; then, converting the first inspection result into a monitoring indicator to obtain a first monitoring indicator; based on this, and using a second monitoring indicator generated by monitoring the availability of the target system, the availability of the target system can be determined according to the first and second monitoring indicators. This technical solution determines system availability by integrating system inspection capabilities with system monitoring capabilities. Specifically, it automatically converts the first inspection result generated by system inspection into a first monitoring indicator, and then combines this with the second monitoring indicator generated by system monitoring to jointly determine the availability of the target system. This expands the monitoring coverage and improves the accuracy of availability determination.

[0021] It should be understood that the description in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1This is a flowchart of an availability determination method provided according to an embodiment of the present invention;

[0024] Figure 2 This is a schematic diagram illustrating an example of availability determination in an availability determination method provided according to an embodiment of the present invention;

[0025] Figure 3 This is a flowchart of another availability determination method provided by an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram illustrating an example of monitoring metric transformation in another availability determination method provided according to an embodiment of the present invention;

[0027] Figure 5 This is a flowchart of another availability determination method provided by an embodiment of the present invention;

[0028] Figure 6 This is a schematic diagram illustrating an application example of a sandbox environment in another availability determination method provided according to an embodiment of the present invention;

[0029] Figure 7 This is a schematic diagram illustrating an example of availability determination in another availability determination method provided according to an embodiment of the present invention;

[0030] Figure 8 This is a structural block diagram of an availability determination device provided according to an embodiment of the present invention;

[0031] Figure 9 This is a schematic diagram of the structure of an electronic device that implements the availability determination method of the present invention. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The same applies to "target," "original," etc., and will not be repeated here. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] Before introducing the embodiments of the present invention, the application scenarios of the embodiments of the present invention will be described by way of example. For example, for a target system running on a hybrid multi-cloud platform, the current main approach is to use a monitoring system to issue monitoring tasks to the target system, so that the target system responds to the monitoring tasks, collects monitoring indicators and reports them to the monitoring system, and then uses these monitoring indicators to determine the availability of the target system. In the embodiments of the present invention, optionally, this can also be referred to as observing the availability of the target system.

[0035] However, practical experience has shown that due to the constant changes in hybrid multi-cloud and complex large-scale cluster environments, the continuous iteration and upgrading of various component services, and the ongoing changes in the various basic services of the supply chain, monitoring cannot cover all elements of the target system, resulting in incomplete monitoring coverage and inaccurate availability determination. Further practical experience has revealed that combining a monitoring system with an inspection system for availability checks of the target system, and integrating the two, can help improve the accuracy of availability determination. The following section will elaborate on the specific implementation of this integration.

[0036] Figure 1 This is a flowchart of an availability determination method provided in an embodiment of the present invention. This embodiment is applicable to determining the availability of a target system, and is particularly applicable to determining the availability of a target system running on a hybrid multi-cloud platform. The method can be executed by the availability determination device provided in this embodiment of the present invention. This device can be implemented in software and / or hardware, and can be integrated into an electronic device, which can be the entire hybrid multi-cloud platform or a part thereof, various user terminals or servers, or one or more clusters based on multiple servers, etc.

[0037] See Figure 1 The method of this invention specifically includes the following steps:

[0038] S110. Obtain the first inspection results generated by performing an availability inspection on the target system.

[0039] The target system can be understood as a system whose availability needs to be determined. Based on this, and in conjunction with the application scenarios that may be involved in the embodiments of the present invention, the system may optionally run on a hybrid multi-cloud platform, a public cloud platform, a private cloud platform, or a containerized platform, which is related to the actual situation and is not specifically limited here; further optionally, the system may implement certain business functions, and therefore may also be called a business system.

[0040] Availability inspections are performed on the target system to obtain a first inspection result during and / or after the inspection. In this embodiment of the invention, optionally, this inspection process can be implemented using a preset inspection program or tool, which can be selected according to actual needs and is not specifically limited here. Taking an inspection program as an example, this inspection program can be understood as a pre-written computer program that can be used to perform availability inspections on the target system. Optionally, this computer program can be distributed to a server where the target system is deployed, so that the computer program can be scheduled and run on the server to perform availability inspections on the target system. Further optionally, the triggering timing of the computer program can be periodic triggering and / or proactive triggering, which can be selected according to actual needs and is not specifically limited here.

[0041] After obtaining the first inspection result, if the first inspection result indicates that the target system is not available, an alarm can be directly triggered based on the inspection notification mechanism, and / or the following steps can be used to feed back to the monitoring system and trigger an alarm based on the monitoring system, etc., without specific limitations.

[0042] S120. The first inspection result is converted into a monitoring index to obtain a first monitoring index, and the availability of the target system is determined based on the first monitoring index and the second monitoring index.

[0043] The second monitoring indicator is generated by monitoring the availability of the target system.

[0044] The second monitoring indicator can be understood as an indicator generated by monitoring the availability of the target system. This indicator can be one or more types, and one indicator can be collected under one indicator. In particular, multiple indicators can be collected, such as multiple indicators that can be collected at different times. These are all related to the actual situation and are not specifically limited here.

[0045] Based on this, as explained above, the second monitoring indicator cannot cover all aspects of the target system. Therefore, in order to increase the monitoring coverage, the first inspection result can be converted into a monitoring indicator to obtain the first monitoring indicator. In this embodiment of the invention, optionally, this conversion process can be achieved by performing semantic recognition on the first inspection result and then converting the obtained semantic recognition result; it can also be achieved by directly converting the first inspection result using a pre-developed conversion program; etc., without specific limitations.

[0046] For the first monitoring indicator obtained above, optionally, the type of the first monitoring indicator can be one or more; further optionally, the type of the first monitoring indicator and the type of the second monitoring indicator can be completely different, partially different, or completely the same. On this basis, further optionally, for the first monitoring indicator and the second monitoring indicator of the same type, the monitoring objects of the two are likely to be different. Here, taking the average load of a certain changed basic service as an example, because of the change, no data points were previously set for the basic service, so the monitoring system cannot monitor the basic service, which leads to the inability to collect the average load of the basic service (i.e., the second monitoring indicator). However, inspection is to inspect what exists, so the basic service can be inspected, and the average load of the basic service (i.e., the first monitoring indicator) can be obtained through monitoring indicator conversion, thereby increasing the monitoring coverage; and so on, without specific limitations.

[0047] Therefore, considering the application scenarios that may be involved in the embodiments of the present invention, optionally, the execution logic such as the acquisition of the first inspection result and the conversion of monitoring indicators can be provided based on an open application programming interface (OpenAPI), that is, exposed in the form of a Hypertext Transfer Protocol (HTTP) interface, so as to be integrated by business parties and indirectly triggered to run. The application of OpenAPI can improve scalability and integration capabilities.

[0048] Furthermore, the availability of the target system is determined by comprehensively analyzing the first and second monitoring indicators. Optionally, in this embodiment of the invention, this determination process is based on monitoring indicators, which are observable; therefore, this determination process can also be called an observation process. Alternatively, this determination process can be performed by an availability determination device, a monitoring system, or, of course, by a system other than the availability determination device and monitoring system (e.g., an analysis system), without specific limitations. Alternatively, in the event of abnormal availability of the target system, an alarm can be triggered using the monitoring system, and further alarms can be triggered in conjunction with the corresponding logs in the first inspection results to facilitate rapid handling of the anomaly. Alternatively, based on availability, the requirements can be determined, and the second monitoring indicator can be aggregated. For example, there could be one second monitoring indicator (i.e., monitoring point) per minute within 6 hours, one monitoring point per minute from 6 to 12 hours, one monitoring point per minute from 12 to 24 hours, and so on. This aggregates multiple monitoring points into one monitoring point in the time dimension. And / or, aggregation can be performed in the label dimension, that is, aggregating monitoring points under different labels into one monitoring point, or converting the data lines formed by multiple labels into a single data line. For example, monitoring points representing the memory usage of network cards in a virtual network. Each network card corresponds to its own label, and one network card corresponds to one data line. When studying the memory usage of a virtual network, the data lines corresponding to each network card can be converted into one data line. This is aggregation in the label dimension.

[0049] The technical solution of this invention involves obtaining a first inspection result generated by performing availability inspection on a target system; then, converting the first inspection result into a monitoring indicator to obtain a first monitoring indicator; based on this, and using a second monitoring indicator generated by monitoring the availability of the target system, the availability of the target system can be determined according to the first and second monitoring indicators. This technical solution determines system availability by integrating system inspection capabilities with system monitoring capabilities. Specifically, it automatically converts the first inspection result generated by system inspection into a first monitoring indicator, and then combines this with the second monitoring indicator generated by system monitoring to jointly determine the availability of the target system. This expands the monitoring coverage and improves the accuracy of availability determination.

[0050] Building upon this, to more vividly illustrate the availability determination process described above, the following is a specific example. For an example, see [link to example]. Figure 2 Both the observation platform (or determination platform) and the target system run on a hybrid multi-cloud platform. The observation platform is built on one or more servers and includes an inspection platform (i.e., a platform with an inspection system deployed) and a monitoring platform (i.e., a platform with a monitoring system deployed). The availability determination device described above also runs on this observation platform.

[0051] Based on this, various inspection procedures are used to inspect the target system and obtain the first inspection result. Then, the corresponding conversion procedure is used to convert the monitoring indicators of the first inspection result to obtain the first monitoring indicator. Then, using the dispatcher component and the collector component, the first monitoring indicator is pushed to the monitoring system, which can be integrated with the second monitoring indicator collected by the monitoring system itself to observe the availability of the target system and push the alarm link of the monitoring system to the end user in case of anomalies.

[0052] An optional technical solution involves a monitoring frequency for the target system that is greater than the inspection frequency for the target system.

[0053] Before determining the availability of the target system based on the first monitoring indicator and the second monitoring indicator, the above availability determination method further includes:

[0054] Based on the monitoring frequency, supplementary monitoring points are added according to the primary monitoring indicator corresponding to multiple inspection times, and the resulting supplementary monitoring indicators are used as the new primary monitoring indicator; or...

[0055] Based on the inspection frequency, the second monitoring indicators obtained at multiple monitoring times are aggregated, and the resulting aggregated monitoring indicators are used as the second monitoring indicators.

[0056] Inspections are typically triggered periodically and / or proactively, differing from the real-time and routine operation of monitoring systems. This results in a continuous time series for conventional monitoring indicators on the monitoring indicator graph, while the monitoring indicators derived from inspections, generated alongside inspection tasks, have a discontinuous time series on the monitoring indicator graph. Therefore, to better integrate the first and second monitoring indicators, their time series need to be aligned, as specifically implemented below.

[0057] Monitoring frequency can be understood as the frequency at which a target system is monitored. Specifically, for two adjacent second monitoring indicators that are of the same type and correspond to the same monitored object in the target system, the monitoring frequency can represent the time interval between the monitoring times corresponding to the two second monitoring indicators, where the monitoring time is the time when the corresponding second monitoring indicator is monitored.

[0058] Similarly, the inspection frequency can be understood as the frequency of inspections of a target system. Specifically, for the first monitoring indicators converted from the first inspection results obtained from two adjacent inspections, if the two first monitoring indicators are of the same type and correspond to the same inspection object in the target system, then the inspection frequency can characterize the time interval between the inspection times corresponding to the two first monitoring indicators.

[0059] Generally speaking, the monitoring frequency is greater than the inspection frequency. Therefore, the time series of the two can be aligned by supplementing the first monitoring indicator or aggregating the second monitoring indicator.

[0060] Specifically, for supplementing the first monitoring indicator, supplementation is carried out based on the monitoring frequency and the first monitoring indicator corresponding to multiple inspection times. For example, supplementation can be carried out using avg_over_time and / or sum_over_time, etc., without specific limitations. For example, assuming the monitoring frequency is 0.1 Hz, meaning the time interval between the monitoring times corresponding to the two second monitoring indicators is 10 seconds, and multiple inspection times include 10:00:00, 10:00:30, and 10:01:00, then supplementary monitoring points can be added between the two first monitoring indicators corresponding to 10:00:00 and 10:00:30 respectively, resulting in supplementary monitoring indicators corresponding to 10:00:10 and 10:00:20; similarly, supplementary monitoring points can be added between the two first monitoring indicators corresponding to 10:00:30 and 10:01:00 respectively, resulting in supplementary monitoring indicators corresponding to 10:00:40 and 10:00:50. Furthermore, each of the obtained supplementary monitoring indicators is used as a new first monitoring indicator to align the time series of the two.

[0061] For aggregating the second monitoring indicator, the second monitoring indicator obtained at multiple monitoring times is aggregated according to the inspection frequency. For example, aggregation can be performed using methods such as `avg_over_time` and / or `sum_over_time`, without specific limitations. For instance, assuming the inspection frequency is 1 / 30Hz, meaning the time interval between the inspection times corresponding to the two first monitoring indicators is 30 seconds, and the multiple monitoring times include 10:00:00, 10:00:10, 10:00:20, 10:00:30, 10:00:40, 10:00:50, and 10:01:00, the second monitoring indicators corresponding to these seven monitoring times can be aggregated into three aggregated monitoring indicators. Furthermore, each aggregated monitoring indicator is used as a second monitoring indicator to align the time series of the two.

[0062] The above technical solution achieves the integrated operation of the first and second monitoring indicators by aligning the time series of the first monitoring indicator on the monitoring indicator legend and the time series of the second monitoring indicator on the monitoring indicator legend, thereby ensuring their consistency.

[0063] Another optional technical solution is that the second monitoring indicator is obtained by the monitoring system. The above availability determination method also includes:

[0064] Obtain the second inspection results generated by the availability inspection of the monitoring system;

[0065] The second inspection results are converted into monitoring indicators to obtain a third monitoring indicator, which is used to determine the availability of the monitoring system.

[0066] In the case of obtaining a second monitoring indicator by monitoring a target system through a monitoring system, the primary prerequisite for obtaining this indicator is that the monitoring system itself is available. Therefore, the availability of the monitoring system itself also needs to be determined. Consequently, the monitoring system can be inspected periodically, for example... Figure 2 The system demonstrates that it performs a routine inspection of the monitoring components of the monitoring system itself to obtain a second inspection result. This second inspection result can then be converted into a third monitoring indicator to determine the availability of the monitoring system.

[0067] The above technical solution uses an inspection and monitoring system, and then converts it into a third monitoring indicator to determine the availability of the monitoring system. This is an important prerequisite for ensuring the effective acquisition of the second monitoring indicator.

[0068] Figure 3 This is a flowchart of another availability determination method provided in this embodiment of the invention. This embodiment is based on and optimized from the above-described technical solutions. In this embodiment, optionally, the monitoring index conversion of the first inspection result is performed to obtain the first monitoring index, including: determining the monitoring index category corresponding to the first inspection result, and determining the target conversion program from a preset set of conversion programs according to the monitoring index category; using the target conversion program to perform monitoring index conversion on the first inspection result to obtain the first monitoring index, wherein the first monitoring index is located under the monitoring index category. The explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0069] See Figure 3 The method in this embodiment may specifically include the following steps:

[0070] S210. Obtain the first inspection results generated by performing an availability inspection on the target system.

[0071] S220. Determine the category of monitoring indicators corresponding to the first inspection result, and determine the target conversion procedure from the preset conversion procedures based on the category of monitoring indicators.

[0072] Here, the monitoring indicator classification can be understood as the category to which the first monitoring indicator belongs after the first inspection result has been converted into a monitoring indicator. The conversion program can be understood as a pre-developed computer program for converting monitoring indicators. In this embodiment of the invention, corresponding conversion programs can be developed for different monitoring indicator classifications to perform the same monitoring indicator conversion process on a class of first inspection results.

[0073] Therefore, the monitoring indicator category corresponding to the first inspection result can be determined. The number of monitoring indicator categories can be one or more. If there are multiple categories, it indicates that the monitoring indicator category is a relatively fine-grained category. This helps to refine the first monitoring indicator and also allows for the subsequent aggregation of the first monitoring indicator, thereby improving the accuracy of usability determination.

[0074] Furthermore, for each monitoring indicator category, a target conversion program corresponding to that monitoring indicator category can be determined from various conversion programs. This target conversion program is the conversion program applicable to converting the monitoring indicators of the first inspection results. Optionally, a mapping relationship identification module can be pre-set. This module can characterize the mapping relationship between various monitoring indicator categories and various conversion programs, thereby allowing the determination of the target conversion program.

[0075] S230. Using a target conversion procedure, the monitoring indicators of the first inspection result are converted to obtain a first monitoring indicator, so as to determine the availability of the target system based on the first monitoring indicator and the second monitoring indicator, wherein the first monitoring indicator is located under the monitoring indicator category.

[0076] The second monitoring indicator is generated by monitoring the availability of the target system.

[0077] After determining the target conversion procedure through the above steps, the target conversion procedure can be run based on the first inspection result. The target conversion procedure can be used to convert the monitoring indicators for the first inspection result, thereby obtaining the first monitoring indicator under the monitoring indicator category corresponding to the target conversion procedure.

[0078] The technical solution of this invention determines the monitoring indicator category corresponding to the first inspection result, and then uses the monitoring indicator category to determine the target conversion program that is compatible with the first inspection result. Thus, the target conversion program can be used to achieve accurate conversion of the monitoring indicators of the first inspection result.

[0079] One optional technical solution involves generating the first inspection result through availability inspection of inspection objects in the target system. Inspection items are pre-defined for each inspection object, and the first inspection result includes inspection data corresponding to each inspection item. The monitoring indicator categories corresponding to the first inspection result are then determined, including:

[0080] For each inspection data, the target item to which the inspection data belongs is determined from each inspection item, and the monitoring indicator classification corresponding to the inspection data is determined according to the target item.

[0081] Accordingly, using the target conversion procedure, the monitoring indicators for the first inspection results are converted to obtain the first monitoring indicator, including:

[0082] Using a target transformation program, the inspection data is transformed into monitoring indicators to obtain the first monitoring indicator.

[0083] The inspection object can be understood as an object in the target system that has an inspection requirement. The number of such objects can be one or more. Such objects can be, for example, databases, central processing units (CPUs) or memory modules, which are related to the actual situation and are not specifically limited here.

[0084] For each inspection target, one or more inspection items are pre-set. These inspection items can be understood as the items that need to be inspected for that target. Taking a database as an example, the inspection items set for the database may include at least one of the following: database structure, database performance, database security, and database backup and recovery. Based on this, the first inspection result obtained for that target may include inspection data corresponding to each inspection item. This inspection data is data that needs to be transformed into monitoring metrics.

[0085] Furthermore, as explained above, different inspection data correspond to specific inspection items, and each inspection item has its own characteristics, which can be mapped to a corresponding monitoring indicator category. Therefore, for each inspection data, the target item to which the inspection data belongs can be determined from each inspection item. Then, the monitoring indicator category corresponding to the inspection data can be determined based on the target item. For example, the monitoring indicator category pre-set for the target item can be used as the monitoring indicator category corresponding to the inspection data. Further, using the target conversion program determined based on the monitoring indicator category, the monitoring indicator is converted for the inspection data to obtain the first monitoring indicator corresponding to the inspection data.

[0086] Based on this, to more vividly understand this technical solution, the following will provide an exemplary illustration with specific examples. For example, see [link to example]. Figure 4The inspection process can be categorized and managed in three levels: inspection template classification, inspection templates, and inspection objects. Inspection template classification and inspection templates are merely for categorization and boundary clarification; they are management-level concepts. Inspection objects, on the other hand, are technical-level concepts. For each inspection object, one or more inspection items can be defined. In this example, these inspection items can also be called inspection feature data items or MonitorFeature items. It's important to note that the transition from inspection object to inspection item is a labeling process. An attribute set, MonitorFeatures, is added to the existing Inspection object. MonitorFeatures contains one or more MonitorFeature items, and each MonitorFeature item consists of key / value pairs. This data structure facilitates dynamic expansion. Furthermore, the MonitorFeature item has a group attribute that identifies the monitoring indicator category it belongs to. The conversion program is designed according to this monitoring indicator category to apply the same monitoring indicator conversion process to a specific type of data.

[0087] Based on this, after obtaining N inspection data points by inspecting the inspection targets, each inspection data point is processed separately. Taking inspection data 1 as an example, we can determine the inspection item to which inspection data 1 belongs (i.e., the target item described above), and then determine the monitoring indicator category marked by the group attribute of the inspection item (…). Figure 4 The system displays monitoring indicator category 1 and monitoring indicator category 2. Then, the mapping relationship identification module is used to determine the conversion program 1 corresponding to monitoring indicator category 1 and the conversion program 2 corresponding to monitoring indicator category 2. Finally, the system uses the conversion program 1 and the conversion program 2 to convert the inspection data 1 into monitoring indicators to obtain the corresponding first monitoring indicator.

[0088] The above technical solution, by breaking down the first inspection result into inspection data corresponding to each inspection item, allows for the determination of corresponding monitoring indicator categories for each inspection data, and then the determination of corresponding target conversion procedures. Furthermore, each target conversion procedure is used to convert the corresponding inspection data into monitoring indicators, thereby improving the conversion accuracy compared to directly converting the first inspection result.

[0089] Another alternative technical solution, after obtaining the first monitoring indicator, further includes the following in the above availability determination method:

[0090] Based on the classification of monitoring indicators, the first monitoring indicator is tagged, and the first monitoring indicator is updated according to the tagging results.

[0091] In practical applications, the volume of monitoring metrics is very large, and the data scale of monitoring metrics formed at the second and minute levels is very large. Therefore, this technical solution processes monitoring metrics through a tagging method (i.e., labeling method), thereby improving the storage, query and analysis capabilities of massive monitoring metrics.

[0092] Based on this, considering that the first monitoring indicators under different monitoring indicator categories each have their own characteristics, that is, the labels they require are different, the first monitoring indicators under each category can be labeled according to the monitoring indicator category, thereby ensuring the accuracy of the labeling. For example, the label for a certain first monitoring indicator can be app="gateway", az="pbsaz", ​​cluster="pbsaz-prod".

[0093] Before introducing the following embodiments, an exemplary application scenario will be provided. Taking an example where both the target system and the availability determination device run on a hybrid multi-cloud platform, to avoid the inspection process and monitoring indicator conversion process affecting the operation of the target system, a sandbox environment can be created on the hybrid multi-cloud platform. This allows the inspection process and monitoring indicator conversion process to be performed within the sandbox environment. Specifically, the sandbox environment is established to meet the isolation, security, and runtime environment management capabilities of business containers (i.e., containers running inspection programs) and platform technology collection capabilities in a hybrid multi-cloud scenario. Essentially, it is based on the Custom Resource Definitions (CRD) and Container Registry (POD, the smallest schedulable resource in Kubernetes) technologies of the Container Orchestration Engine (Kubernetes). By enhancing resource isolation and security boundaries, it achieves strong isolation in a multi-tenant environment and unified management of the code runtime environment, preventing unknown anomalies during technology collection from damaging the target system.

[0094] Within the running container, the container image can be shared with the host file system through the Virtual File System (VFS). Independent virtual network cards are allocated to sandbox containers, system calls are converted into user-space operations, and the host-level docker.socket channel is mounted to the execution container. The sa account is created at the cluster level for role-based access control (RBAC) authorization. The permissions of the collection layer container are restricted based on SecurityContext control technology. All interactions with the business container are conducted through file exchange, avoiding system process interference and port duplication.

[0095] Next, we will mainly use the conversion of monitoring metrics in a sandbox environment as an example to illustrate this.

[0096] Figure 5 This is a flowchart of another availability determination method provided in this embodiment of the invention. This embodiment is an optimization based on the above-described technical solutions. In this embodiment, optionally, the target system runs on a target platform, and the above-described availability determination method may further include: creating a sandbox environment on the target platform; distributing various conversion programs to the sandbox environment, so that in the sandbox environment, the steps of determining the target conversion program from the various conversion programs are executed, and the steps of obtaining a first monitoring indicator using the target conversion program are executed. The explanations of terms that are the same as or corresponding to those in the above embodiments will not be repeated here.

[0097] See Figure 5 The method in this embodiment may specifically include the following steps:

[0098] S310. For the target system running on the target platform, obtain the first inspection result generated by the availability inspection of the target system.

[0099] The target platform can be understood as a platform running a target system, or more specifically, a platform running a target system and availability determination devices. This platform can be, for example, a hybrid multi-cloud platform, a public cloud platform, a private cloud platform, or a containerized platform, depending on the actual situation, and no specific limitation is made here.

[0100] S320. Create a sandbox environment on the target platform and distribute various conversion programs to the sandbox environment so that S330-S340 can be executed in the sandbox environment.

[0101] In this process, a sandbox environment is created on the target platform, and various conversion programs are distributed to the sandbox environment. This ensures the isolation between the running environment of the conversion programs distributed to the sandbox environment and the target platform, thereby ensuring the security of the conversion programs and the target system.

[0102] In this embodiment of the invention, optionally, the sandbox environment can be represented by a Pod; that is, the sandbox environment can be understood as a Pod runtime environment launched by an availability determination device, i.e., a black box environment. Further optionally, see [link to relevant documentation]. Figure 6 The Pod contains an inspection initialization container for initializing inspections, an inspection execution container for executing inspection programs, and a sidecar container for monitoring metric conversion. This sidecar container can also be called a monitoring sidecar container.

[0103] Run S330-S340 in the sandbox environment to obtain the first monitoring metric. For example, here we continue with... Figure 6For example, after generating an inspection task based on the inspection template, the inspection execution process can be triggered by issuing the inspection task. The inspection execution process first creates a Pod, then runs each container in the Pod to perform the corresponding operations, and after obtaining the first monitoring indicator, the first monitoring indicator can be reported to the monitoring system through the monitoring component of the monitoring system itself to determine availability.

[0104] S330. Determine the category of monitoring indicators corresponding to the first inspection result, and determine the target conversion procedure from the various conversion procedures that have been issued based on the category of monitoring indicators.

[0105] S340. Using a target conversion procedure, the monitoring indicators of the first inspection result are converted to obtain a first monitoring indicator, so as to determine the availability of the target system based on the first monitoring indicator and the second monitoring indicator, wherein the first monitoring indicator is located under the monitoring indicator category.

[0106] The second monitoring indicator is generated by monitoring the availability of the target system.

[0107] The technical solution of this invention creates a sandbox environment on a target platform running a target system and distributes various conversion programs into the sandbox environment, thereby ensuring the isolation between the running environment of the conversion program and the target platform, and thus ensuring the security of the operation of the conversion program and the target system.

[0108] An optional technical solution, the above-mentioned availability determination method, further includes:

[0109] Pull up the sidecar container in a sandbox environment;

[0110] Various conversion programs are deployed to the sandbox environment, including:

[0111] Various conversion programs are distributed to the sidecar container so that by running the sidecar container, the steps of determining the target conversion program from the various conversion programs are executed, and the steps of obtaining the first monitoring indicator using the target conversion program are executed.

[0112] Specifically, a sidecar container is dynamically launched within a sandbox environment, and various transformation programs are then deployed to this sidecar container. This allows for the transformation of monitoring metrics by running the sidecar container. The use of the sidecar container further ensures the isolation between the transformation program's runtime environment and the target platform, thereby further guaranteeing the security of both the transformation program's operation and the target system's operation.

[0113] Based on this, optionally, the availability of the target system is determined according to the first monitoring indicator and the second monitoring indicator, including:

[0114] By running the sidecar container, the first monitoring metric is reported to the monitoring system, so that the monitoring system can determine the availability of the target system based on the first monitoring metric and the second monitoring metric.

[0115] Specifically, by running a sidecar container, the first monitoring metric obtained from that container is reported to the monitoring system. For example, the first monitoring metric can be sent to the dispatcher component via an HTTP request, and then the collector component collects the first monitoring metric and reports it to the monitoring system. In this way, the monitoring system can determine the availability of the target system based on the first and second monitoring metrics.

[0116] The above technical solution, through the sidecar container, enables the reporting of the first monitoring indicator to the monitoring system, thereby enabling it to work with the monitoring system to determine the availability of the target system.

[0117] Alternatively, if the first monitoring indicator is obtained using the sidecar container, the above-described method of labeling the first monitoring indicator according to the monitoring indicator classification includes:

[0118] For the preset label program embedded in the sidecar container, the first label is obtained by running the sidecar container and executing the preset label program.

[0119] Based on the classification of monitoring indicators, a second label is determined, and the first monitoring indicator is tagged according to the first and second labels.

[0120] The preset tagging program can be understood as a predefined computer program (or code snippet) used to characterize what kind of tag to be applied to the first monitoring indicator. This preset tagging program is embedded in a sidecar container, which provides the execution environment for the program. Therefore, by running the sidecar container, the preset tagging program can be executed to obtain the first tag, which is the tag to be applied to the first monitoring indicator. Based on this, and considering the application scenarios that may be involved in this embodiment, optionally, the availability determination device can provide a monitoring software development kit (SDK). Business users can call this monitoring SDK to embed the preset tagging program into the sidecar container using a hook, thereby facilitating the embedding of a custom first tag into the first monitoring indicator. For example, some middleware inspection tasks require the first monitoring indicator to have an example name for the embedded inspection instance so that it can be displayed in subsequent monitoring indicator alarm chains.

[0121] Based on the classification of monitoring indicators, a second label is determined that needs to be applied to the first monitoring indicator. Then, the first monitoring indicator can be tagged based on the first and second labels.

[0122] The above technical solution allows business users to embed custom first tags into the first monitoring metric by embedding the preset tag program into the sidecar container, thereby better meeting business needs.

[0123] Building upon this foundation, to better understand the creation, application, and recycling process of sandbox environments as a whole, the following is an exemplary illustration with specific examples. The exemplary implementation process is as follows:

[0124] 1. The observation platform or OpenAPI caller triggers the sandbox environment creation task.

[0125] 2. In response to the sandbox environment creation task, create custom resources (CRs) in each Kubernetes cluster of the hybrid multi-cloud platform. It should be noted that the sandbox environment CRD is the description file definition of the sandbox environment; the sandbox environment CR is the instantiated manifestation of the sandbox environment CRD, used to describe the received sandbox creation content, reflecting the characteristics and fields that the current sandbox environment should possess. This can be YAML-style descriptive information. A typical sandbox environment CR may include information such as sandbox name, trigger source, task name, creator, creation time, running image address, sidecar image address, initialization (init) image address, context environment variable parameter set, integrated environment runtime language, data collection entry configuration file, monitoring metric classification, monitoring metric conversion rules, and data collection result recording path.

[0126] 3. Sandbox CR Operator Processing. When a sandbox CR is created, Kubernetes can trigger a listening signal. Upon receiving the signal, the sandbox CR Operator will begin interpreting the CR information of the sandbox environment, creating Pods according to the CR fields, configuring Pod Spec information, and then creating containers, as follows:

[0127] The first type sets up a corresponding public image based on task characteristics to create an inspection initialization container. This inspection initialization container can also be called an init sidecar container. Typically, this type of container can also be named Sandbox-Checker-Init container. The main responsibility of this type of container is to create an initialization environment, call the platform layer interface, and pull dynamic configuration parameters into the container context to form an execution environment. Subsequent containers can perform their respective business processing based on the context parameters of this environment.

[0128] The second type is to create a business-mode running container (i.e., a business container). The base image of this container will also be set as the platform's public image. Based on the characteristics of the business program in CR, an appropriate public image will be configured and environment parameters will be set to schedule the business program to run.

[0129] The third category is the result processing and hook program runtime environment container. This container is usually named the Sandbox-Checker-Exec container, which is also a platform-level container, similar to the monitoring sidecar container described above. It is responsible for collecting execution results and creating hook interfaces to call third-party services. This container is also the execution environment for converting inspection results into monitoring metrics. The execution environment includes information such as the inspection results generated by the aforementioned inspection tasks, environment parameters, context environment variable parameter sets, monitoring metric categories, monitoring metric conversion rules, and the path for recording collection results. Based on this, the corresponding inspection result collection program and conversion program are scheduled for execution. After successful monitoring metric conversion, the data is first written to local memory, and the monitoring platform's dispatcher component is called in real time to push the monitoring metrics according to the dispatcher HTTP API interface specification. For monitoring metrics that fail to call the push interface, the execution status can be marked, and the memory status results are periodically flushed to the local disk to avoid the loss of monitoring metrics due to memory fluctuations.

[0130] 4. The final step in the sandbox environment is to use the `Sandbox-Checker-Exec` container to mark all tasks as completed, exit the execution environment, and set the Pod's exit status code to 0. Subsequent resource reclamation can then be handled by Kubernetes' own mechanisms. At this point, the creation, application, and reclamation of the sandbox environment are complete.

[0131] Based on this, in order to better understand the various technical solutions described above as a whole, the following examples will be provided for illustration. For example, see [link to example]. Figure 7 The specific implementation process is as follows:

[0132] 1. For each inspection object, identify the corresponding inspection item, and classify each inspection item. For example, on a hybrid multi-cloud platform, it can be divided into computing, storage, network, system, capacity, virtual machine, container or hardware awareness, etc.

[0133] 2. Based on step 1, the inspection item can be mapped to a certain monitoring indicator category, and then to a certain conversion program to form a mapping relationship identification module.

[0134] At this point, the preparation phase is complete, and the next step is the application phase.

[0135] 3. Various conversion programs run in a sandbox environment as sidecars. Based on this, for each inspection data, the corresponding inspection item can be determined, and then the corresponding monitoring indicator category can be determined. Then, the mapping relationship identification module is used to identify the conversion program corresponding to the monitoring indicator category, and the corresponding sidecar container is run in the sandbox environment to convert the inspection data and obtain the first monitoring indicator.

[0136] 4. Utilize dynamic labeling capabilities to dynamically label the primary monitoring indicator.

[0137] 5. Report the first monitoring metric to the dispatcher component of the monitoring system. In this example, optionally, different conversion programs can correspond to different dispatcher components.

[0138] 6. The collector component of the monitoring system collects the first monitoring indicators reported by the inspection team, adds platform layer identifiers and marks source information for traceability.

[0139] 7. The monitoring system can combine the reported first monitoring indicator with the second monitoring indicator it collects to observe availability, and trigger alarms and follow the alarm chain when an anomaly occurs.

[0140] In the example above, considering that inspection and monitoring have different perspectives—inspection focuses on task execution and results, while monitoring focuses on metrics—the transition from inspection to monitoring requires converting the task execution process and result expression into metric form. Specifically, this can be metric name, tag set, and metric value, which can then be integrated with the monitoring metrics collected by the monitoring system to determine usability.

[0141] Figure 8 This is a structural block diagram of an availability determination apparatus provided in an embodiment of the present invention. This apparatus is used to execute the availability determination method provided in any of the above embodiments. This apparatus and the availability determination methods of the above embodiments belong to the same inventive concept. Details not described in detail in the embodiments of the availability determination apparatus can be found in the embodiments of the availability determination methods described above. See also... Figure 8 The device may specifically include: a first inspection result acquisition module 410 and an availability determination module 420.

[0142] The first inspection result acquisition module 410 is used to acquire the first inspection result generated by performing an availability inspection on the target system.

[0143] The availability determination module 420 is used to convert the first inspection result into a monitoring index to obtain a first monitoring index, so as to determine the availability of the target system based on the first monitoring index and the second monitoring index.

[0144] The second monitoring indicator is generated by monitoring the availability of the target system.

[0145] Optionally, the availability determination module 420 may include:

[0146] The target conversion program determination submodule is used to determine the monitoring indicator category corresponding to the first inspection result, and to determine the target conversion program from the preset conversion programs based on the monitoring indicator category.

[0147] The first monitoring indicator acquisition submodule is used to convert the first inspection result into a monitoring indicator using the target conversion program, thereby obtaining the first monitoring indicator, which is located under the monitoring indicator category.

[0148] Based on this, optionally, the first inspection result is generated by performing availability inspections on the inspection objects in the target system. Inspection items are pre-set for the inspection objects, and the first inspection result includes inspection data corresponding to each inspection item. Then, the target conversion program determining submodule may include:

[0149] The monitoring indicator classification and determination unit is used to determine the target item to which the inspection data belongs from each inspection item for each inspection data, and to determine the monitoring indicator classification corresponding to the inspection data based on the target item.

[0150] Correspondingly, the first monitoring metric is obtained by the sub-module, which is specifically used for:

[0151] Using a target transformation program, the inspection data is transformed into monitoring indicators to obtain the first monitoring indicator.

[0152] Alternatively, if the target system runs on a target platform, the aforementioned availability determination device may further include:

[0153] The sandbox environment creation module is used to create a sandbox environment on the target platform;

[0154] The conversion program distribution module is used to distribute various conversion programs to the sandbox environment, so that in the sandbox environment, the steps of determining the target conversion program from various conversion programs are executed, and the steps of obtaining the first monitoring indicator using the target conversion program are executed.

[0155] Optionally, the availability determination device described above may further include:

[0156] Sidecar container pull-up module, used to pull up sidecar containers in a sandbox environment;

[0157] Correspondingly, the conversion program distribution module is specifically used for:

[0158] Various conversion programs are distributed to the sidecar container so that by running the sidecar container, the steps of determining the target conversion program from the various conversion programs are executed, and the steps of obtaining the first monitoring indicator using the target conversion program are executed.

[0159] Based on this, the availability determination module 420 may optionally include:

[0160] The availability determination unit can be used to report a first monitoring indicator to the monitoring system by running a sidecar container, so that the monitoring system can determine the availability of the target system based on the first monitoring indicator and the second monitoring indicator.

[0161] Optionally, based on any of the above-described devices, the availability determination device may further include:

[0162] The first monitoring indicator update module is used to, after obtaining the first monitoring indicator, label the first monitoring indicator according to the monitoring indicator classification, and update the first monitoring indicator based on the labeling results.

[0163] Based on this, optionally, the first monitoring metric is obtained using the sidecar container, then the first monitoring metric update module may include:

[0164] The first tag obtaining unit is used to obtain the first tag by running the sidecar container and executing the preset tag program for the preset tag program embedded in the sidecar container;

[0165] The first monitoring indicator labeling unit is used to determine the second label based on the classification of monitoring indicators, and to label the first monitoring indicator based on the first label and the second label.

[0166] Optionally, if the monitoring frequency corresponding to the target system is greater than the inspection frequency corresponding to the target system, then the above-mentioned availability determination device further includes:

[0167] The first monitoring indicator addition module is used to supplement the monitoring points according to the monitoring frequency and based on the first monitoring indicators corresponding to multiple inspection times before determining the availability of the target system based on the first monitoring indicators and the second monitoring indicators, and to use the supplemented monitoring indicators as the new first monitoring indicators.

[0168] Or,

[0169] The second monitoring indicator update module is used to aggregate the second monitoring indicators obtained at multiple monitoring times according to the inspection frequency before determining the availability of the target system based on the first and second monitoring indicators, and then use the aggregated monitoring indicators as the second monitoring indicators.

[0170] Optionally, the second monitoring indicator is obtained by the monitoring system, and the aforementioned availability determination device may further include:

[0171] The second inspection result acquisition module is used to acquire the second inspection results generated by the availability inspection of the monitoring system.

[0172] The availability analysis module is used to convert the second inspection results into monitoring indicators to obtain a third monitoring indicator, and to determine the availability of the monitoring system based on the third monitoring indicator.

[0173] The availability determination device provided in this embodiment of the invention acquires a first inspection result generated by performing an availability inspection on a target system through a first inspection result acquisition module. Then, through an availability determination module, the first inspection result is converted into a monitoring index to obtain a first monitoring index. Based on this, the availability of the target system can be determined by combining the first monitoring index with the second monitoring index generated by monitoring the availability of the target system. This device determines system availability by integrating system inspection capabilities with system monitoring capabilities. Specifically, it automatically converts the first inspection result generated by the system inspection into a first monitoring index, and then combines it with the second monitoring index generated by system monitoring to jointly determine the availability of the target system. This expands the monitoring coverage and improves the accuracy of availability determination.

[0174] The availability determination apparatus provided in the embodiments of the present invention can execute the availability determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0175] It is worth noting that in the embodiments of the above availability determination device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0176] Figure 9 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0177] like Figure 9 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0178] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0179] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as availability determination methods.

[0180] In some embodiments, the availability determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the availability determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the availability determination method by any other suitable means (e.g., by means of firmware).

[0181] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0182] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0183] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0184] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0185] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0186] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0187] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0188] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0189] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining availability, characterized in that, include: Obtain the first inspection results generated by performing availability inspections on the target system; The first inspection result is converted into a monitoring index to obtain a first monitoring index, and the availability of the target system is determined based on the first monitoring index and the second monitoring index. The second monitoring indicator is generated by monitoring the availability of the target system.

2. The method according to claim 1, characterized in that, The step of converting the first inspection result into a monitoring indicator to obtain the first monitoring indicator includes: Determine the monitoring indicator category corresponding to the first inspection result, and determine the target conversion program from the preset conversion programs based on the monitoring indicator category; Using the target conversion program, the monitoring indicators of the first inspection result are converted to obtain the first monitoring indicator, wherein the first monitoring indicator is located under the monitoring indicator category.

3. The method according to claim 2, characterized in that, The first inspection result is generated by performing availability inspection on the inspection objects in the target system. Inspection items are pre-set for the inspection objects, and the first inspection result includes inspection data corresponding to each of the inspection items. The step of determining the classification of monitoring indicators corresponding to the first inspection result includes: For each of the inspection data, the target item to which the inspection data belongs is determined from each of the inspection items, and the monitoring indicator classification corresponding to the inspection data is determined according to the target item; The step of using the target conversion program to convert the first inspection result into a monitoring indicator to obtain a first monitoring indicator includes: Using the target conversion program, the inspection data is converted into monitoring indicators to obtain the first monitoring indicator.

4. The method according to claim 2, characterized in that, The target system runs on the target platform, and the method further includes: Create a sandbox environment on the target platform; The various conversion programs are distributed to the sandbox environment, where the steps of determining the target conversion program from the various conversion programs are performed, and the steps of obtaining the first monitoring indicator using the target conversion program are performed.

5. The method according to claim 4, characterized in that, Also includes: Pull up the sidecar container in the sandbox environment; The step of distributing various conversion programs to the sandbox environment, and in the sandbox environment, performing the step of determining the target conversion program from the various conversion programs, and performing the step of obtaining the first monitoring indicator using the target conversion program, includes: The various conversion programs are distributed to the sidecar container, so that by running the sidecar container, the steps of determining the target conversion program from the various conversion programs are performed, and the steps of obtaining the first monitoring indicator using the target conversion program are performed.

6. The method according to claim 5, characterized in that, Determining the availability of the target system based on the first monitoring indicator and the second monitoring indicator includes: By running the sidecar container, the first monitoring metric is reported to the monitoring system, so that the monitoring system can determine the availability of the target system based on the first and second monitoring metrics.

7. The method according to any one of claims 2-6, characterized in that, After obtaining the first monitoring indicator, the process also includes: According to the classification of the monitoring indicators, the first monitoring indicator is tagged, and the first monitoring indicator is updated based on the tagging results.

8. The method according to claim 7, characterized in that, The first monitoring indicator is obtained using the sidecar container. The step of classifying the monitoring indicator and tagging the first monitoring indicator includes: For the preset label program embedded in the sidecar container, the first label is obtained by running the sidecar container and executing the preset label program; Based on the classification of the monitoring indicators, a second label is determined, and the first monitoring indicator is tagged according to the first label and the second label.

9. The method according to claim 1, characterized in that, If the monitoring frequency corresponding to the target system is greater than the inspection frequency corresponding to the target system, then before determining the availability of the target system based on the first monitoring indicator and the second monitoring indicator, the method further includes: Based on the monitoring frequency and the first monitoring indicator corresponding to multiple inspection times, supplementary monitoring points are added, and the resulting supplementary monitoring indicators are used as the new first monitoring indicator; or... According to the inspection frequency, the second monitoring index obtained at multiple monitoring times is aggregated, and the resulting aggregated monitoring index is used as the second monitoring index.

10. The method according to claim 1, characterized in that, The second monitoring indicator is obtained by the monitoring system, and the method further includes: Obtain the second inspection result generated by performing an availability inspection on the monitoring system; The second inspection result is converted into a monitoring index to obtain a third monitoring index, and the availability of the monitoring system is determined based on the third monitoring index.

11. An availability determination device, characterized in that, include: The first inspection result acquisition module is used to acquire the first inspection result generated by the availability inspection of the target system. The availability determination module is used to convert the first inspection result into a monitoring index to obtain a first monitoring index, so as to determine the availability of the target system based on the first monitoring index and the second monitoring index. The second monitoring indicator is generated by monitoring the availability of the target system.

12. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to cause the at least one processor to perform the availability determination method as described in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the availability determination method as described in any one of claims 1-10.

14. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the availability determination method as described in any one of claims 1-10.

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